Determining the popularity of a Web service or application can be an important question whose relevance continues to grow with increasing commercialization of the Internet. Knowing how many clients are accessing a Web server at any point in time can be a useful measure for a number of reasons. For example, in addition to helping with classical network or Web-server traffic engineering and capacity planning tasks, identifying the number of clients accessing a Web server also may reflect the popularity of a given service or application hosted at the Web server. A high popularity (or a lack of popularity) can directly affect the marketing potential of a given application or service. Given that online advertising has become an important factor in the business model of today's Internet, the measurement of a popularity of the service or application may directly impact the cost of advertisements at the service or application. The cost of advertisements at the service or application directly impacts revenues derived from the service or application.
Without having administrative access or privileges to server or network logs that track access to a service or application (and therefore, the popularity of the service or application), the independent auditing of a claim of a certain popularity of a service or application can be difficult. Some known systems (e.g., Alexa, comScore, Google Trends, and the like) rely on “crowd-sourcing” methods. Such crowd-sourcing methods attempt to indirectly measure the popularity of a service or application. For example, crowd-sourcing methods can estimate the popularity of a service or application by collecting browsing statistics of a subset of Internet users accessing or using the service or application.
Crowd-sourcing methods of measuring popularity of a service or application can involve a subset of Internet clients installing typically “free” toolbars or other software applications on the clients to collect user browsing statistics. The toolbars or other applications collect and report these statistics, which may be used to quantify the popularity of various services or applications. One problem with crowd-sourcing methods is that the measurement methods typically are not comprehensive as the methods rely only on a subset of end users. Consequently, such methods can provide popularity estimates with unknown error bounds. As a result, the accuracy of such crowd-sourcing methods has been called into question. Empirical measurements used to examine the accuracy of the crowd-sourcing methods have found that the crowd-sourcing methods can generate striking discrepancies relative to ground truth data and may have a fundamental inability to accurately estimate trends in the popularity of a service or application.
A need exists for the independent measurement or relatively accurate estimation of the popularity or traffic of a service or application hosted on a Web server without having administrative access or privileges to the Web server or server logs.